# Deep-Unfolded Massive Grant-Free Transmission in Cell-Free Wireless Communication Systems

arXiv: https://arxiv.org/abs/2502.13390 · HTML: https://mlsanity.com/paper/2502.13390/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 70 references that are in the map.
- First posted on arXiv 19 Feb 2025.

## Builds on (most cited first, 28 of 28)

- [Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures](https://mlsanity.com/paper/1409.2574/) (2014)
- [Deep Unfolding for Communications Systems: A Survey and Some New Directions](https://mlsanity.com/paper/1906.05774/) (2019)
- [What Will 5G Be?](https://mlsanity.com/paper/1405.2957/) (2014)
- [Scalable Cell-Free Massive MIMO Systems](https://mlsanity.com/paper/1908.03119/) (2019)
- [Massive Access for 5G and Beyond](https://mlsanity.com/paper/2002.03491/) (2020)
- [Clustering-Based Activity Detection Algorithms for Grant-Free Random Access in Cell-Free Massive MIMO](https://mlsanity.com/paper/2111.15378/) (2021)
- [1-bit Massive MU-MIMO Precoding in VLSI](https://mlsanity.com/paper/1702.03449/) (2017)
- [Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication](https://mlsanity.com/paper/2311.06770/) (2023)
- [Massive Access in Cell-Free Massive MIMO-Based Internet of Things: Cloud Computing and Edge Computing Paradigms](https://mlsanity.com/paper/2007.09617/) (2020)
- [A Random Access Protocol for Pilot Allocation in Crowded Massive MIMO Systems](https://mlsanity.com/paper/1604.04248/) (2016)
- [Joint Activity Detection, Channel Estimation, and Data Decoding for Grant-free Massive Random Access](https://mlsanity.com/paper/2107.05246/) (2021)
- [Joint Channel Estimation and Data Detection in Cell-Free Massive MU-MIMO Systems](https://mlsanity.com/paper/2110.15928/) (2021)
- [Joint Activity Detection and Channel Estimation in Cell-Free Massive MIMO Networks with Massive Connectivity](https://mlsanity.com/paper/2112.13013/) (2021)
- [Active Terminal Identification, Channel Estimation, and Signal Detection for Grant-Free NOMA-OTFS in LEO Satellite Internet-of-Things](https://mlsanity.com/paper/2201.02084/) (2022)
- [Rate-Splitting assisted Massive Machine-Type Communications in Cell-Free Massive MIMO](https://mlsanity.com/paper/2201.07508/) (2022)
- [Asynchronous Activity Detection for Cell-Free Massive MIMO: From Centralized to Distributed Algorithms](https://mlsanity.com/paper/2210.00451/) (2022)
- [Model-Driven Deep Learning for Non-Coherent Massive Machine-Type Communications](https://mlsanity.com/paper/2301.00516/) (2023)
- [Hybrid Knowledge-Data Driven Channel Semantic Acquisition and Beamforming for Cell-Free Massive MIMO](https://mlsanity.com/paper/2307.03070/) (2023)
- [Grant-Free Access via Bilinear Inference for Cell-Free MIMO with Low-Coherent Pilots](https://mlsanity.com/paper/2009.12863/) (2020)
- [Soft-Output Joint Channel Estimation and Data Detection using Deep Unfolding](https://mlsanity.com/paper/2112.00330/) (2021)
- [Mitigating Smart Jammers in Multi-User MIMO](https://mlsanity.com/paper/2208.01453/) (2022)
- [Joint Device Activity Detection, Channel Estimation and Signal Detection for Massive Grant-free Access via BiGAMP](https://mlsanity.com/paper/2304.00744/) (2023)
- [Deep-Unfolded Joint Activity and Data Detection for Grant-Free Transmission in Cell-Free Systems](https://mlsanity.com/paper/2312.12874/) (2023)
- [Two-Stage Channel Estimation Approach for Cell-Free IoT With Massive Random Access](https://mlsanity.com/paper/2109.13450/) (2021)
- [Deep Learning for Asynchronous Massive Access with Data Frame Length Diversity](https://mlsanity.com/paper/2305.07278/) (2023)
- [Joint Device Identification, Channel Estimation, and Signal Detection for LEO Satellite-Enabled Random Access](https://mlsanity.com/paper/2308.03556/) (2023)
- [Joint Active User Detection, Channel Estimation, and Data Detection for Massive Grant-Free Transmission in Cell-Free Systems](https://mlsanity.com/paper/2308.14637/) (2023)
- [Low-Coherence Sequence Design Under PAPR Constraints](https://mlsanity.com/paper/2407.21400/) (2024)

## Built on by (most cited first, 1 of 1)

- [Generative Diffusion Model Driven Massive Random Access in Massive MIMO Systems](https://mlsanity.com/paper/2505.12382/) (2025)

## Abstract (arXiv)

Grant-free transmission and cell-free communication are vital in improving coverage and quality-of-service for massive machine-type communication. This paper proposes a novel framework of joint active user detection, channel estimation, and data detection (JACD) for massive grant-free transmission in cell-free wireless communication systems. We formulate JACD as an optimization problem and solve it approximately using forward-backward splitting. To deal with the discrete symbol constraint, we relax the discrete constellation to its convex hull and propose two approaches that promote solutions from the constellation set. To reduce complexity, we replace costly computations with approximate shrinkage operations and approximate posterior mean estimator computations. To improve active user detection (AUD) performance, we introduce a soft-output AUD module that considers both the data estimates and channel conditions. To jointly optimize all algorithm hyper-parameters and to improve JACD performance, we further deploy deep unfolding together with a momentum strategy, resulting in two algorithms called DU-ABC and DU-POEM. Finally, we demonstrate the efficacy of the proposed JACD algorithms via extensive system simulations.